We have developed a new computational framework for merging odor response data sets from heterogeneous studies, creating a consensus metadatabase, the database of odor responses (DoOR). As a result, we obtained a functional atlas of all available odor responses in Drosophila melanogaster. Both the program and the data set are freely accessible and downloadable on the Internet (http://neuro.uni-konstanz.de/DoOR). The procedure can be adapted to other species, thus creating a family of “olfactomes” in the near future. Drosophila melanogaster was chosen because of all species this one is closest to having the complete olfactome characterized, with the highest number of deorphanized receptors available. The database guarantees long-term stability (by offering time-stamped, downloadable versions), up-to-date accuracy (by including new data sets as soon as they are published), and portability (for other species). We hope that this comprehensive repository of odor response profiles will be useful to the olfactory community and to computational neuroscientists alike.

BackgroundPlants under herbivore attack release volatiles that attract natural enemies, and herbivores in turn avoid such plants. Whilst herbivore-induced plant volatile blends appeared to reduce the attractiveness of host plants to herbivores, the volatiles that are key in this process and particularly the way in which deterrence is coded in the olfactory system are largely unknown. Here we demonstrate that herbivore-induced cotton volatiles suppress orientation of the moth Spodoptera littoralis to host plants and mates.ResultsWe found that (E)-4,8-dimethyl-1,3,7-nonatriene (DMNT), an induced volatile, is key in herbivore deterrence: DMNT suppressed plant odour- and pheromone-induced behaviours. We then dissected the neurophysiological basis of this interaction. DMNT-responding glomeruli were also activated by other plant compounds, suggesting that S. littoralis possesses no segregated olfactory circuit dedicated exclusively to DMNT. Instead, DMNT suppressed responses to the main pheromone component, (Z)-9-(E)-11-tetradecenyl acetate, and primarily to (Z)-3-hexenyl acetate, a host plant attractant.ConclusionOur study shows that olfactory sensory inhibition, which has previously been reported without reference to an animal’s ecology, can be at the core of coding of ecologically relevant odours. As DMNT attracts natural enemies and deters herbivores, it may be useful in the development or enhancement of push-pull strategies for sustainable agriculture.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-015-0188-3) contains supplementary material, which is available to authorized users.

An adaptive transition from exploring the environment in search of vital resources to exploiting these resources once the search was successful is important to all animals. Here we study the neuronal circuitry that allows larval Drosophila melanogaster of either sex to negotiate this exploration-exploitation transition. We do so by combining Pavlovian conditioning with high-resolution behavioral tracking, optogenetic manipulation of individually identified neurons, and EM data-based analyses of synaptic organization. We find that optogenetic activation of the dopaminergic neuron DAN-i1 can both establish memory during training and acutely terminate learned search behavior in a subsequent recall test. Its activation leaves innate behavior unaffected, however. Specifically, DAN-i1 activation can establish associative memories of opposite valence after paired and unpaired training with odor, and its activation during the recall test can terminate the search behavior resulting from either of these memories. Our results further suggest that in its behavioral significance DAN-i1 activation resembles, but does not equal, sugar reward. Dendrogram analyses of all the synaptic connections between DAN-i1 and its two main targets, the Kenyon cells and the mushroom body output neuron MBON-i1, further suggest that the DAN-i1 signals during training and during the recall test could be delivered to the Kenyon cells and to MBON-i1, respectively, within previously unrecognized, locally confined branching structures. This would provide an elegant circuit motif to terminate search on its successful completion.

Background: Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consisting of co-regulated genes. A growing pool of publicly available microarray datasets allows the identification of modules by monitoring expression changes over time. These time-series datasets can be searched for gene expression modules by one of the many clustering methods published to date. For an integrative analysis, several time-series datasets can be joined into a three-dimensional gene-condition-time dataset, to which standard clustering or biclustering methods are, however, not applicable. We thus devise a probabilistic clustering algorithm for gene-condition-time datasets.